75 citations · 179 across the 9 of their papers we have counts for
12 papers
Wrist Photoplethysmography Predicts Dietary Information
Kyle Verrier, Achille Nazaret, Joseph Futoma +2
Whether wearable photoplethysmography (PPG) contains dietary information remains unknown. We trained a language model on 1.1M meals to predict meal descriptions from PPG, aligning…
Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions
Eray Erturk, Fahad Kamran, Salar Abbaspourazad +6
Wearable devices record physiological and behavioral signals that can improve health predictions. While foundation models are increasingly used for such predictions, they have been…
Wearable Accelerometer Foundation Models for Health via Knowledge Distillation
Salar Abbaspourazad, Anshuman Mishra, Joseph Futoma +2
Modern wearable devices can conveniently record various biosignals in the many different environments of daily living, enabling a rich view of individual health. However, not all b…
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance
Andrew C. Miller, Leon A. Gatys, Joseph Futoma +1
Machine learning models now commonly developed to screen, diagnose, or predict health conditions are evaluated with a variety of performance metrics. An important first ste…
Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs
Jianzhun Du, Joseph Futoma, Finale Doshi-Velez
We present two elegant solutions for modeling continuous-time dynamics, in a novel model-based reinforcement learning (RL) framework for semi-Markov decision processes (SMDPs), usi…
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions
Omer Gottesman, Joseph Futoma, Yao Liu +4
Off-policy evaluation in reinforcement learning offers the chance of using observational data to improve future outcomes in domains such as healthcare and education, but safe deplo…